Wireless communication systems have been used to carry voice traffic and low data rate non-voice traffic. Current wireless communication systems can also carry high data rate multimedia traffic, such as video, data, and other types of traffic. Multimedia Broadcast and Multicast Service (MBMS) channels may be used to transmit streaming applications, such as radio broadcast, television broadcast, movies, and other types of audio or video contents.
The multimedia broadcast multicast service is defined in the Third Generation Partnership Project (3GPP) Release 6 documentation. The standard TS22.146 defines the high level service requirements of the MBMS, and the standard TS22.246 defines typical service scenarios. MBMS services allow user equipment (UE) such as mobile telephones or other mobile terminals to receive services from service providers via a network. MBMS is a packet service (PS) domain service for transferring multimedia data such as audio, pictures, video, etc, to a plurality of terminals using a unidirectional point-to-multipoint bearer service. The services are generally delivered in a packet format, currently in the form of IP Internet protocol (IP) packets. The services are typically provided by the service providers to a radio network controller that controls how the services are delivered to mobile terminals within the network. The radio network controller typically schedules the transmission of services according to network resources and other factors.
As MBMS is a multimedia service, multiple services of different Quality of Service (QoS) or multiple streams of different QoS in a same service may be provided to a single UE or to different UEs. In addition, MBMS transmission mechanisms are typically needed to support variable source data-rates. In other words, source data may vary in transmission rates and bit error rates (BERs).
Since the MBMS channel is unidirectional, a transmitting base station cannot acknowledge any reception error at a UE. Therefore, means of information protection is desirable.
For consideration of information protection, transmission of a modulated information signal over a wireless communication channel requires selection of appropriate methods for protecting the information in the modulated signal. Such methods may comprise, for example, encoding, symbol repetition, interleaving, and other known methods.
For broadcast/multicast services, the characteristics and requirements of the broadcast/multicast services are specified by 3GPP MBMS and the related broadcast/multicast service layer functions. Simultaneous distribution of different content data may be required in a MBMS service and simultaneous reception of more than one MBMS service for one terminal may be required. MBMS transport services may vary, for instance, in QoS parameters. In such cases, unequal error protection mechanisms (UEP) are typically required to support various different QoS for the high data rate communication for MBMS services in wireless systems. In the following description, data with higher quality requirement and/or lower rate requirement are defined as the higher priority data and data with lower quality requirement and/or higher rate requirement are defined as the lower priority data.
Two types of methods have been applied for UEP. One type comprises applying a more powerful conventional error-correcting code to the higher priority data. The other type comprises using non-uniformly spaced modulation constellation or hierarchical modulation to provide unequal protection for the data with different priorities. U.S. Pat. No. 5,105,442 describes coded modulation that may achieve both power-efficiency and bandwidth-efficiency by combining the above two methods.
U.S. Pat. No. 5,214,656 describes combining the coded modulation with a time division multiplexing scheme. Signals with different priorities are separately coded and modulated. The modulated signals with different priorities are then mapped to different time-slots.
The above mentioned methods may provide good performance of unbalanced data transmission but have limited capacity due to their single transmit antenna configuration.
In current technologies, Multiple Input Multiple Output (MIMO) communication systems employ multiple antennas at a transmitter and/or a receiver to improve coverage, quality and capacity. Therefore, one possible way to increase the system capacity of a MBMS system is to use multiple antennas to perform space-time (ST) processing. The concept of combining space-time processing with conventional UEP techniques may be employed to achieve more capacity and better quality.
One method of UEP, described in C. H. Kuo, et al., ‘Robust video transmission over wideband wireless channel using space-time coded OFDM system’, WCNC 2002, vol. 3. March 2002, comprises concatenating forward error correction (FEC) with ST code in MIMO systems. In this method, more robustness is provided to the data with higher priority by adopting more powerful FEC. However, the embedded ST code does not provide differentiation between data with different priorities. Therefore, one problem that may arise is that this kind of concatenation with the unified space-time processing cannot provide further differentiation between data with different priorities and thus, limited protection levels can be supported. Another problem is that it is practically complex to implement this method since for each input data, a space time coder is separately applied.
Yet other methods based on combining different space-time technologies have been proposed for UEP in MIMO systems. See for example, Muhammad Farooq Sabir, Robert W. Heath Jr, and Alan C. Bovik “An unequal error protection scheme for multiple input multiple output systems”, IEEE Asilomar Conference on Signals, Systems and Computers, vol 1, pp. 575-579, November 2002; and, C. H. Kuo, et al., “Embedded space-time coding for wireless broadcast with heterogeneous receivers”, Globecom 2000, vol 21, November, 2000. However, since these proposed systems require a change of the coding structure of the space time coder for every different protection requirements and, can only provide specific rates and specific protection levels when the space-time coders are selected, these systems are low in flexibility and are highly complex.
For concatenation codes used in channel coding and space-time coding, turbo codes using an iterative decoding technique are provided as a high-reliable channel coding technique for third generation wireless communication in the International Mobile Telecommunications-2000 (IMT-2000) standard. The turbo codes may perform the coding operation by using parallel concatenated recursive systematic convolutional (RSC) codes and perform the decoding operation using the iterative decoding technique. In addition, the turbo codes represent superior performance approaching the so-called Shannon's limitation with respect to a BER if an interleaver size is made larger and the iterative decoding is sufficiently performed. However, if the turbo codes are employed, one problem that may arise is that the number of operations may increase resulting in high complexity. Another problem that may arise is that as both the size of the interleaver and the number of iterative decoding operations increase, a time delay may occur making a real time process difficult.
Beyond 3G, fourth generation wireless communication systems are being developed in order to provide better voice and high-speed multimedia services. In such systems, a channel coding technique called low density parity check (LDPC) code is being used. The LDPC code has superior coding characteristics as compared to conventional turbo codes, with respect to complexity and performance. The LDPC code is typically a linear block code in which most elements of a parity check matrix (H) are “0”. It has been discovered that the LDPC code can provide superior performance if, e.g., a probabilistic coding technique of the LDPC is used.
The LDPC code is defined by a random parity check matrix H in which the number of element “1” in the matrix is sparsely distributed and the rest of the elements are all zeros. The parity check matrix H is typically a matrix for determining if coding is correctly performed with regard to a reception signal. For example, if a value obtained through multiplying a coded reception signal by the parity check matrix H is “0”, there is no error in the coding. In the following description, row weight (or row degree) is defined by the number of 1's in a row of the parity check matrix H, and column weight (or column degree) is defined by the number of 1's in a column. Unless otherwise specified, degree refers to column degree in the following description.
The LDPC code may be described by both a matrix and a factor graph. The LDPC code may be decoded in a factor graph using an iterative decoding algorithm based on a sum-product algorithm. The decoder, employing the LDPC code, is less complex than a decoder using turbo code. Furthermore, a parallel processing decoder can be easily embodied. Therefore, a space-time encoder/decoder may have superior channel coding/decoding performance if the space-time encoder/decoder performs coding/decoding operations using the LDPC code.
There are current methods used for UEP by implementing LDPC codes for channel coding. These methods typically map information bits and parity bits to different parts of a codeword by employing a property that different connection degrees of data nodes can provide different error protection. See for example, Xiumei Yang, et. al, “New research on unequal error protection (UEP) property of Irregular LDPC codes”, Consumer Communications and Networking Conference, 2004. First IEEE 5-8 Jan. 2004 Page(s):361-363, and Poulliat C., Declercq D., Fijalkow I., Optimization of LDPC codes for UEP channels, in Proc. IEEE International Symposium on Information Theory (ISIT'04), p. 450, Chicago, Ill., USA, June 2004. For such methods, application of the LDPC codes is typically restricted because construction of the parity check matrix structure is practically difficult. Further, the performance diversity achieved for different level bits is typically low since different code rates cannot be realized for different information bits.
Further, “New results on unequal error protection using LDPC codes”, IEEE Communication letters, vol. 10, no. 1, January 2006 describes yet another LDPC-based method that relates to combining two Tanner graphs. However, there is no further explanation in the document on how to construct a sub-block to generate a usable parity check matrix.
In view of the above, transmission techniques that may simultaneously support various error protection requirements in high rate data transmission, e.g. MBMS services, at high system flexibility and low implementation complexity are desired.
Hence, there exists a need for a method and system for data transmission in a multiple input multiple output (MIMO) system to address at least one of the above problems.